{"id":"W2051499747","doi":"10.1145/2559206.2581135","title":"A brief technical note on haptic jellyfish with Falcon and OpenGL","year":2014,"lang":"en","type":"article","venue":"","topic":"Teleoperation and Haptic Systems","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Jellyfish; OpenGL; Computer science; Focus (optics); Marine engineering; Haptic technology; Computer graphics (images); Work (physics); Simulation; Engineering; Artificial intelligence; Ecology; Physics; Visualization; Biology; Mechanical engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007304421,0.0007434708,0.0003702341,0.0006061725,0.0006879672,0.002150729,0.001593709,0.001205262,0.032619],"category_scores_gemma":[0.001632829,0.0007130461,0.0005346049,0.0005332431,0.0007017135,0.002848719,0.002253072,0.002192813,0.007277146],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006461955,"about_ca_system_score_gemma":0.0006770916,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00271226,"about_ca_topic_score_gemma":0.002688039,"domain_scores_codex":[0.9987343,0.00009592648,0.00008116407,0.0001380975,0.0008440327,0.000106458],"domain_scores_gemma":[0.9993624,0.0001568752,0.00003419566,0.0001359062,0.0002189208,0.00009168765],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004834309,0.00011698,0.00191848,0.001010491,0.00004789788,0.003241186,0.001190744,0.009162221,0.1744744,0.1400385,0.07092386,0.5973918],"study_design_scores_gemma":[0.00003206086,0.000264657,0.001137904,0.0002300047,0.0000230673,0.003277363,0.0001586036,0.04123265,0.03720526,0.01451327,0.9018141,0.0001111283],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01055862,0.003639946,0.8831537,0.002437046,0.001386602,0.000213847,0.0002954873,0.01374691,0.08456784],"genre_scores_gemma":[0.1645494,0.006333602,0.6644209,0.001364905,0.0007773517,0.000395347,0.001236412,0.004483498,0.1564386],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.032619,"threshold_uncertainty_score":0.1091214,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007053565625353054,"score_gpt":0.1993429448572454,"score_spread":0.1922893792318923,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}